Metadata Association Across Cloud Providers
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Solution Overview
Problem
In distributed computing environments, metadata associated with database objects is often missing, incomplete, or inaccurate, especially when resources are provisioned by multiple providers, leading to challenges in resource management and system reconstruction during malfunctions or disasters.
Innovation Solution
A system is developed to identify resources with missing or incomplete metadata, generate a user interface for selecting and associating appropriate metadata, and enable bulk tagging of resources with declarative tags or other metadata, ensuring complete, consistent, and accurate metadata association across the network, regardless of the provider.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If metadata is manually added or corrected for each resource, then metadata accuracy is improved, but time consumption and operational complexity increase significantly
Solution Approach 1:
The system enables self-service by automatically discovering resources and generating metadata without requiring manual intervention. The metadata generation module autonomously creates metadata records by querying resource identifiers and attributes, allowing the system to service itself rather than relying on manual metadata addition for each resource.
Solution Approach 2:
The system performs preliminary action by pre-generating metadata records before they are needed for resource management operations. The metadata generation module proactively creates and stores metadata in the database, so that when resources need to be managed or reconstructed, the metadata is already available, eliminating the need for time-consuming manual addition at the moment of need.
2Measurement precision
If metadata is manually added or corrected for each resource, then metadata accuracy is improved, but operational complexity increases significantly
Solution Approach 1:
The system enables self-service by automatically discovering resources and generating metadata without requiring manual intervention. The metadata generation module autonomously creates metadata records by querying resource identifiers and attributes, allowing the system to service itself rather than relying on manual metadata addition for each resource.
Solution Approach 2:
The system achieves universality by creating a centralized metadata generation module that serves multiple functions: discovering resources across different providers, generating metadata records, storing metadata in a unified database, and supporting various resource management operations. This single multi-functional module replaces the need for separate manual processes for each resource type and provider.
3Adaptability or versatility
If resources are provisioned by multiple providers, then system versatility and scalability are improved, but metadata consistency and accuracy deteriorate
Solution Approach 1:
The system introduces an intermediary metadata generation module that acts as a mediator between multiple resource providers and the resource management system. This intermediary standardizes metadata generation by applying uniform discovery and generation rules across all providers, ensuring consistent metadata format and quality regardless of the source provider, thereby resolving the inconsistency problem while maintaining multi-provider versatility.
Solution Approach 2:
The system achieves universality by creating a centralized metadata generation module that serves multiple functions: discovering resources across different providers, generating metadata records, storing metadata in a unified database, and supporting various resource management operations. This single multi-functional module replaces the need for separate manual processes for each resource type and provider.
4Reliability
If complete and accurate metadata is ensured for all resources, then resource management effectiveness and system reconstruction capability are improved, but the complexity of metadata management increases
Solution Approach 1:
The system applies segmentation by dividing the metadata management process into distinct modular components: a discovery module that identifies resources, a generation module that creates metadata records, a storage component that stores metadata in a database, and a management interface that handles operations. This segmentation reduces overall complexity by making each component independent and manageable while ensuring complete and accurate metadata through coordinated operation of all segments.
Solution Approach 2:
The system introduces an intermediary metadata generation module that acts as a mediator between multiple resource providers and the resource management system. This intermediary standardizes metadata generation by applying uniform discovery and generation rules across all providers, ensuring consistent metadata format and quality regardless of the source provider, thereby resolving the inconsistency problem while maintaining multi-provider versatility.
Data Source
AI summary
Systems, apparatuses, and methods for modifying metadata associated with database objects obtained from providers, such as cloud providers, are disclosed. Modifying metadata associated with database objects obtained from cloud providers may include identifying resources in a computer network that originate from providers, such as cloud providers that do not have associated metadata. A user interface that includes the resources may be generated, and the resource may receive input to select the resources and a descriptor that may be associated with the resources. The selected resources may then be associated, in a configuration management dataset, with metadata derived from the selected descriptor. The metadata may indicate an association of the selected resources to a parameter.